Face recognition techniques oftentimes are used to locate, identify, or verify one or more persons appearing in images in an image collection. In a typical face recognition approach, faces are detected in the images; the detected faces are normalized; features are extracted from the normalized faces; and the identities of persons appearing in the images are identified or verified based on comparisons of the extracted features with features that were extracted from faces in one or more query images or reference images. Many automatic face recognition techniques can achieve modest recognition accuracy rates with respect to frontal images of faces that are accurately registered; however, when applied to other facial views (poses), poorly registered facial images, faces with large area of occlusion, poorly illuminated facial images or faces belonging to special population groups (e.g., babies and seniors), these techniques typically fail to achieve acceptable recognition accuracy rates.
What are needed are systems and methods that are capable of detecting and recognizing face images with wide variations in pose, illumination, expression, occlusion, aging, and population groups.